Soft decision audio decoding system

ABSTRACT

A soft decision audio decoding system for preserving audio continuity in a digital wireless audio receiver is provided that deduces the likelihood of errors in a received digital signal, based on generated hard bits and soft bits. The soft bits may be utilized by a soft audio decoder to determine whether the digital signal should be decoded or muted. The soft bits may be generated based on the detected point and a detected noise power, or by using a soft-output Viterbi algorithm. The value of the soft bits may indicate confidence in the strength of the hard bit generation. The soft decision audio decoding system may infer errors and decode perceptually acceptable audio without requiring error detection, as in conventional systems, as well as have low latency and improved granularity.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional of U.S. Non-Provisional patentapplication Ser. No. 16/030,545, filed on Jul. 9, 2018, which is adivisional of U.S. Non-Provisional patent application Ser. No.14/844,632, filed on Sep. 3, 2015, now U.S. Pat. No. 10,019,223 issuedon Jul. 10, 2018, all of which are fully incorporated herein byreference.

TECHNICAL FIELD

This application generally relates to a soft decision audio decodingsystem. In particular, this application relates to a soft decision audiodecoding system for preserving audio continuity in a digital wirelessaudio receiver by deducing the likelihood of errors in a receiveddigital signal with low latency and improved granularity.

BACKGROUND

Audio production can involve the use of many components, includingmicrophones, wireless audio transmitters, wireless audio receivers,recorders, and/or mixers for capturing, recording, and presenting thesound of productions, such as television programs, newscasts, movies,live events, and other types of productions. The microphones typicallycapture the sound of the production, which is wirelessly transmittedfrom the microphones and/or the wireless audio transmitters to thewireless audio receivers. The wireless audio receivers can be connectedto a recorder and/or a mixer for recording and/or mixing the sound by acrew member, such as a production sound mixer. Electronic devices, suchas computers and smartphones, may be connected to the recorder and/ormixer to allow the crew member to monitor audio levels and timecodes.

Wireless audio transmitters, wireless audio receivers, wirelessmicrophones, and other portable wireless communication devices includeantennas for transmitting radio frequency (RF) signals which containdigital or analog signals, such as modulated audio signals, datasignals, and/or control signals. Users of portable wirelesscommunication devices include stage performers, singers, actors, newsreporters, and the like. A wireless audio transmitter may transmit an RFsignal that includes an audio signal to a wireless audio receiver. Thewireless audio transmitter may be included in a wireless handheldmicrophone, for example, that is held by the user and includes anintegrated transmitter and antenna. When the RF signal is received atthe wireless audio receiver, the RF signal may be degraded due tointerference. This degradation may cause the RF signal to have a poorsignal-to-noise ratio (SNR), which results in bit errors that can causeaudio artifacts. Typically, when significant audio artifacts arepresent, the output audio is muted. However, muting the output audio isundesirable in many situations and environments. The effects of suchinterference are most prevalent in harsh RF environments where physicaland electrical factors influence the transmission and reception of RFsignals, e.g., movement of the microphone within the environment, otherRF signals, etc.

In a conventional wireless audio system, error detection techniques aretypically utilized, e.g., parity checking such as a cyclic redundancycheck (CRC), to determine whether bit errors are present in a digitalsignal received in an RF signal at a wireless receiver. Such errordetection involves analyzing the digital signal at the transmitter,generating and adding parity information to the data when it istransmitted, and recalculating the parity of the received data at thereceiver. If the recalculated parity does not match the transmittedparity, then it can be determined that there are bit errors in the data.While such error detection is relatively straightforward and easy toimplement, it is not optimal in wireless audio systems in particularenvironments, such as when maintaining the continuity of the outputaudio is critical.

In particular, conventional error detection may result in an increasedlatency due to the recalculation of the parity of the data at thereceiver. Conventional error detection also suffers from poorgranularity and is typically unable to specify which bits of the dataare errors, which may result in the discarding of large amounts of dataand undesirable audio dropouts or mutes in the output audio. As atradeoff, it is possible to decrease the size of the data beingtransmitted to reduce the latency and improve the granularityattributable to conventional error detection. However, by decreasing thesize of the data being transmitted, more frequent parity calculationsand transmissions would be needed with a significant cost to bandwidth.Furthermore, conventional error detection techniques typically havelimitations of the number of errors that can be detected. In particular,parity checking may only reliably detect a certain number of errorswithin the data. If the data has more than this threshold number oferrors, the parity check may still deemed to have passed, in some cases.

Accordingly, there is an opportunity for a soft decision audio decodingsystem that addresses these concerns. More particularly, there is anopportunity for a soft decision audio decoding system that preservesaudio continuity in a digital wireless audio receiver by deducing thelikelihood of errors in a received digital signal with low latency andimproved granularity.

SUMMARY

The invention is intended to solve the above-noted problems by providingsoft decision audio decoding systems and methods that are designed to,among other things: (1) generate hard bits and soft bits in a digitalwireless audio receiver; (2) determine whether to decode the digitalsignal into a digital audio signal, based on the soft bits; and (3)maintain audio continuity while reducing latency and improvinggranularity.

In an embodiment, a method of receiving an audio signal represented by adigital signal may include detecting a point of a constellationassociated with a digital modulation scheme in the digital signal from areceived RF signal; detecting a noise power of the digital signal;generating hard bits based on the detected point of the constellation;generating soft bits based on the detected point of the constellationand the detected noise power; determining whether to decode the digitalsignal into a digital audio signal, based on the soft bits; generatingthe digital audio signal based on the digital signal, if it isdetermined to decode the digital signal into the digital audio signal;and muting the digital audio signal, if it is determine not to decodethe digital signal into the digital audio signal.

In another embodiment, a method of receiving an audio signal representedby a digital signal may include detecting a sequence of symbols of aconstellation associated with a digital modulation scheme in the digitalsignal from a received RF signal, wherein the sequence of symbolsrepresents bits of the audio signal; determining a likely transmittedsequence of symbols based on error in the complex plane determined fromrunning the detected sequence of symbols through a Viterbi algorithm;generating hard bits based on the determined likely transmitted sequenceof symbols; generating soft bits based on a degree of closeness of thesequence of symbols to known legal sequences of symbols determined fromrunning the sequence of symbols through a soft-output Viterbi algorithm;determining whether to decode the digital signal into a digital audiosignal, based on the soft bits; generating the digital audio signalbased on the digital signal, if it is determined to decode the digitalsignal into the digital audio signal; and muting the digital audiosignal, if it is determine not to decode the digital signal into thedigital audio signal.

In a further embodiment, a method of receiving an audio signalrepresented by a digital signal may include detecting a phase trajectoryassociated with a partial response non-linear phase modulation scheme inthe digital signal from a received RF signal; determining a likelytransmitted phase trajectory based on running the detected phasetrajectory through a Viterbi algorithm; determining a likely transmittedphase trajectory based on running the detected phase trajectory througha Viterbi algorithm; generating soft bits based on a degree of closenessof the phase trajectory to known legal phase trajectories determinedfrom running the phase trajectory through a soft-output Viterbialgorithm; determining whether to decode the digital signal into adigital audio signal, based on the soft bits; generating the digitalaudio signal based on the digital signal, if it is determined to decodethe digital signal into the digital audio signal; and muting the digitalaudio signal, if it is determine not to decode the digital signal intothe digital audio signal.

These and other embodiments, and various permutations and aspects, willbecome apparent and be more fully understood from the following detaileddescription and accompanying drawings, which set forth illustrativeembodiments that are indicative of the various ways in which theprinciples of the invention may be employed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a wireless audio receiver including a softdecision audio decoding system, in accordance with some embodiments.

FIG. 2 is a flowchart illustrating operations for receiving an audiosignal represented by a digital signal modulated by a linear digitalmodulation scheme using a soft decision audio decoding system in awireless audio receiver, in accordance with some embodiments.

FIG. 3 is a flowchart illustrating operations for receiving an audiosignal represented by a digital signal modulated by a linear digitalmodulation scheme using a soft decision audio decoding system in awireless audio receiver, in accordance with some embodiments.

FIG. 4 is a flowchart illustrating operations for receiving an audiosignal represented by a digital signal modulated by a partial responsenon-linear phase modulation scheme using a soft decision audio decodingsystem in a wireless audio receiver, in accordance with someembodiments.

FIG. 5 is a flowchart illustrating operations for determining whether todecode a digital signal that includes coded audio based on frequencyresponse using a soft decision audio decoding system in a wireless audioreceiver, in accordance with some embodiments.

FIG. 6 is a flowchart illustrating operations for determining whether todecode a digital signal that includes coded audio based onsignal-to-noise ratio using a soft decision audio decoding system in awireless audio receiver, in accordance with some embodiments.

FIG. 7 is a flowchart illustrating operations for determining whether todecode a digital signal that includes PCM audio using a soft decisionaudio decoding system in a wireless audio receiver, in accordance withsome embodiments.

DETAILED DESCRIPTION

The description that follows describes, illustrates and exemplifies oneor more particular embodiments of the invention in accordance with itsprinciples. This description is not provided to limit the invention tothe embodiments described herein, but rather to explain and teach theprinciples of the invention in such a way to enable one of ordinaryskill in the art to understand these principles and, with thatunderstanding, be able to apply them to practice not only theembodiments described herein, but also other embodiments that may cometo mind in accordance with these principles. The scope of the inventionis intended to cover all such embodiments that may fall within the scopeof the appended claims, either literally or under the doctrine ofequivalents.

It should be noted that in the description and drawings, like orsubstantially similar elements may be labeled with the same referencenumerals. However, sometimes these elements may be labeled withdiffering numbers, such as, for example, in cases where such labelingfacilitates a more clear description. Additionally, the drawings setforth herein are not necessarily drawn to scale, and in some instancesproportions may have been exaggerated to more clearly depict certainfeatures. Such labeling and drawing practices do not necessarilyimplicate an underlying substantive purpose. As stated above, thespecification is intended to be taken as a whole and interpreted inaccordance with the principles of the invention as taught herein andunderstood to one of ordinary skill in the art.

The soft decision audio decoding system described herein can be utilizedin a digital wireless audio receiver to preserve audio continuity bydeducing the likelihood of errors in a received digital signal with lowlatency and improved granularity. Hard bits and soft bits generated inthe receiver are utilized by a soft audio decoder to determine whetherthe digital signal should be decoded or muted. In some embodiments, whena linear modulation scheme has been utilized, the hard bits may begenerated based on a detected point (i.e., symbol) in a constellationassociated with a digital modulation scheme of the digital signal. Thevalue of the hard bits may be determined based on the distance betweenthe detected point and defined points of the constellation. The softbits may be generated based on the detected point, distance to thedefined points of the constellation, and a detected noise power of thedigital signal. In other embodiment, the hard bits may be generatedbased on a detected sequence of symbols that represents bits of theaudio signal that is run through a Viterbi algorithm to determine alikely transmitted sequence of symbols. The soft bits may be generatedbased on a degree of closeness of the sequence of symbols to known legalsequences determined from running the sequence of symbols through asoft-output Viterbi algorithm for trellis-coded modulation. When anon-linear modulation scheme has been utilized, the hard bits may begenerated based on a detected phase trajectory that is run through aViterbi algorithm to determine a likely transmitted phase trajectory.The soft bits may be generated based on a degree of closeness of thephase trajectory to known legal phase trajectories determined fromrunning the phase trajectory through a soft-output Viterbi algorithm.Additionally, in both linear and non-linear modulation schemes used indigital wireless audio systems applying forward error correction (FEC),soft-input, soft-output decoders can be applied to further refine thesoft bit information prior to decoding the digital signal into audio.

Regardless of whether a linear or non-linear modulation scheme has beenutilized, the value of the soft bits may indicate confidence in thestrength of the hard bit generation. The soft audio decoder maydetermine whether to decode or mute the digital signal, based on thesoft bits. Accordingly, the soft decision audio decoding system mayinfer errors and decode perceptually acceptable audio from the digitalsignal without requiring error detection, as in conventional systems.

Furthermore, because the soft decision audio decoding system hasimproved granularity by generating confidence information (i.e., thesoft bits) on a bit-wise basis, the impact of short duration errors isminimized. In other words, if the soft audio decoder decides to mute theaudio based on the soft bits, then such audio muting may be relativelyshort and imperceptible (or at least perceptually acceptable andpreferable to a mute) because of its short duration. In addition, thebit-wise confidence information of the soft bits allows differentclasses of data within the same payload of data to be independentlyhandled and processed. For example, when audio codecs are deployed,codewords comprised of bits of differing perceptual importance may beenabled through use of the soft decision audio decoding system, such asdescribed in concurrently-filed and commonly owned patent application“Multiresolution Coding and Modulation System” (U.S. patent applicationSer. No. 14/844,678), which is incorporated herein by reference in itsentirety.

FIG. 1 is an exemplary block diagram of a wireless audio receiver 100that includes a soft decision audio decoding system. The wireless audioreceiver 100 may receive a transmitted RF signal that contains an audiosignal from an audio source, such as a microphone or playback device.The wireless audio receiver 100 may process the received RF signal toproduce an output analog audio signal 116. In some embodiments, thewireless audio receiver 100 may produce an output digital audio signal.The wireless audio receiver may be a rack mountable unit, portable unit,and/or camera mountable unit, in some embodiments. Processes 200 and 300that may use the wireless audio receiver 100 are respectively shown inFIGS. 2 and 3. In particular, the wireless audio receiver 100 and theprocesses 200, 300, 400 may utilize the soft decision audio decodingsystem to ensure continuity of audio that is transmitted wirelessly.Various components included in the wireless audio receiver 100 may beimplemented using software executable by one or more servers orcomputers, such as a computing device with a processor and memory,and/or by hardware (e.g., discrete logic circuits, application specificintegrated circuits (ASIC), programmable gate arrays (PGA), fieldprogrammable gate arrays (FPGA), etc.

The transmitted RF signal may be received by a receiving antenna 102.The received RF signal may be sampled and converted into a digitalsignal by an analog to digital converter 104, and the digital signal maybe provided to a detector 106. The digital modulation scheme may includelinear modulation schemes, such as quadrature amplitude modulation (QAM)or quadrature phase shift keying (QPSK), and partial response non-linearmodulation schemes, such as continuous phase modulation (CPM), forexample.

With regards to linear modulation schemes, the embodiment described bythe process 200 shown in FIG. 2 may be utilized by the soft decisionaudio decoding system of the wireless audio receiver 100. In particular,the detector 106 may detect a point (i.e., symbol) in the digital signalthat corresponds to a constellation associated with a digital modulationscheme being utilized, such as at step 202 of the process 200. Theconstellation associated with the digital modulation scheme mayrepresent how a signal may be modulated in the complex plane (i.e., within-phase (I) and quadrature (Q) axes). In ideal conditions, the point(i.e., symbol) detected in the received digital signal would exactlymatch the point in the transmitted RF signal. However, due tointerference, the digital signal may have been degraded so that thepoint may not be exactly the same as in the transmitted RF signal.

The detector 106 may also detect the noise power of the digital signal,such as at step 204 of the process 200. The noise power may be detectedby analyzing the perturbation of known symbols (e.g., pilots) embeddedby the wireless transmitter within the digital symbol stream. The noisepower may represent the presence of interference and/or the noise floorof the system. The magnitude of the perturbation may therefore representthe magnitude of the interference and/or noise. The perturbation of theknown symbols may be defined as the distance between the received symboland a known point of the constellation. The noise power σ² can may becalculated based on the equation

${\sigma^{2} = {\frac{1}{N}*\Sigma{{{rx}_{i} - {pilot}_{i}}}^{2}}},$

where N is the number of pilot symbols in an observation interval,rx_(i) is the received symbol, and pilot_(i) is the expected symbol.

The detected point and the detected noise power may be provided from thedetector 106 to a demodulator 108 in the wireless audio receiver 100.The demodulator 108 may generate hard bits based on the detected pointof the constellation, such as at step 206 of the process 200. The valueof the hard bits may be 0 or 1, and be determined based on a distance ofthe detected point of the constellation to a defined point of theconstellation. In particular, the value of the hard bits may bedetermined as the defined point of the constellation that is closest indistance to the detected point of the constellation.

The demodulator 108 may also generate soft bits based on the detectedpoint of the constellation and the detected noise power, such as at step208 of the process 200. The soft bits may represent the confidence inthe strength of the hard bit generation, and be calculated as a loglikelihood ratio. The log likelihood ratio may be determined based on anestimate of the noise power relative to a normalized constellation. Inparticular, the log likelihood ratio may be calculated based on thedistance of the detected point of the constellation to an opposing pointof the constellation, and be scaled by the detected noise power σ². Theopposing point of the constellation may be a point of the constellationthat represents an opposite result, e.g., 0, as compared to the detectedpoint, e.g., 1. The magnitude of the log likelihood ratio may be lowerwhen the detected noise power is higher, and conversely, the magnitudeof the log likelihood ratio may be higher when the detected noise poweris lower. The approximate log likelihood ratio L for a given bit b maybe calculated based on the equation

${{L_{approx}(b)} = {- {\frac{1}{\sigma^{2}}\left\lbrack {{\min_{s \in S_{0}}\left( {\left( {x - s_{x}} \right)^{2} + \left( {y - s_{y}} \right)^{2}} \right)} - {\min_{s \in S_{1}}\left( {\left( {x - s_{x}} \right)^{2} + \left( {y - s_{y}} \right)^{2}} \right)}} \right\rbrack}}},$

where x and y represent the complex plane coordinates of the detectedpoint and s_(x) and s_(y) represent the coordinates of the points of theconstellation that represent when a bit is a 0 (S₀) or a 1 (S₁). Theremaining steps 210-216 of the process 200 are described below.

In another embodiment related to linear modulation schemes, theembodiment described by the process 300 shown in FIG. 3 may be utilizedby the soft decision audio decoding system of the wireless audioreceiver 100. In this embodiment, trellis-coded modulation may beutilized to map bits (representing audio) to symbols such that thesequence of the symbols that is transmitted is constrained. Withtrellis-coded modulation, the symbols of the constellation do notthemselves represent bits, but rather, the sequence of the symbolsrepresents bits. A Viterbi algorithm determines from the receivedsequence of symbols the most likely transmitted sequence of symbols andgenerates the hard bits based on the likely transmitted sequence ofsymbols. Soft bits, i.e., a log likelihood ratio, may be generated by asoft-output Viterbi algorithm, as is known in the art. The soft bits mayrepresent the confidence in the strength of the hard bit generation,based upon the degree of closeness of the decoded sequence of symbols toknown legal sequences of symbols.

In particular, the detector 106 may detect a sequence of symbols in thedigital signal, such as at step 302 of the process 300. In idealconditions, the detected sequence of symbols would exactly match thetransmitted sequence of symbols, but the digital signal may have beendegraded (due to interference) so that the detected sequence of symbolsis not exactly the same. The detected sequence of symbols may beprovided from the detector 106 to the demodulator 108. The demodulator108 may determine a likely transmitted sequence of symbols by runningthe detected sequence of symbols through a Viterbi algorithm, such as atstep 304 of the process 300. The likely transmitted sequence of symbolsmay be determined based on the degree of error in the complex planebetween the detected sequence of symbols and known sequences of symbols.

The demodulator 108 may generate hard bits based on the likelytransmitted sequence of symbols, such as at step 306 of the process 300.The value of the hard bits may be 0 or 1. The demodulator 108 may alsogenerate soft bits based on running the detected sequence of symbolsthrough a soft-output Viterbi algorithm, such as at step 308 of theprocess 300. The soft bits may be determined based on a degree ofcloseness of the detected sequence of symbols to known legal sequencesof symbols. The remaining steps 310-316 of the process 300 are describedbelow.

With regards to partial response non-linear phase modulation schemes,the embodiment described by the process 400 shown in FIG. 4 may beutilized by the soft decision audio decoding system of the wirelessaudio receiver 100. In this embodiment, the bits (representing audio)may determine the phase trajectory of the transmitted signal. The phasetrajectory is constrained by the partial response parameters of thesystem. A Viterbi algorithm determines from the received phasetrajectory the most likely transmitted phase trajectory and generatesthe hard bits based on the likely transmitted phase trajectory. Softbits, i.e., a log likelihood ratio, may be generated by a soft-outputViterbi algorithm, as is known in the art. The soft bits may representthe confidence in the strength of the hard bit generation, based uponthe degree of closeness of the detected phase trajectory to known legalphase trajectories.

In particular, the detector 106 may detect a phase trajectory in thedigital signal, such as at step 402 of the process 400. In idealconditions, the detected phase trajectory would exactly match thetransmitted phase trajectory, but the digital signal may have beendegraded (due to interference) so that the detected phase trajectory isnot exactly the same. The detected phase trajectory may be provided fromthe detector 106 to the demodulator 108. The demodulator 108 maydetermine a likely transmitted phase trajectory by running the detectedphase trajectory through a Viterbi algorithm, such as at step 404 of theprocess 400.

The demodulator 108 may generate hard bits based on the likelytransmitted phase trajectory, such as at step 406 of the process 400.The value of the hard bits may be 0 or 1. The demodulator 108 may alsogenerate soft bits based on running the detected phase trajectorythrough a soft-output Viterbi algorithm, such as at step 408 of theprocess 400. The soft bits may be determined based on a degree ofcloseness of the detected phase trajectory to known legal phasetrajectories. The remaining steps 410-416 of the process 400 aredescribed below.

In some embodiments, the processes 200, 300, 400 may also include theability to utilize soft-input, soft-output forward error correction(FEC) codes, as is known in the art, to further refine the generatedsoft bits. In particular, prior to transmission, the transmitter mayencode the digital bit stream with FEC. The receiver 100 may include anFEC decoder that receives the digital signal that has been encoded withFEC. The FEC decoder may also receive the generated soft bits, andattempt to recover the original digital bit stream. The generated softbits may be modified by the FEC decoder so that the soft audio decoder110 determines whether to decode the digital signal into the digitalaudio signal, based on the modified soft bits.

In the processes 200, 300, 400, the log likelihood ratios generated atsteps 208, 308, 408, respectively, may be a positive, zero, or negativevalue. If the log likelihood ratio is zero, then there is equalconfidence in the hard bit being a 0 or 1. If the log likelihood ratiois positive, then there is greater confidence that the hard bit is 0,and conversely, if the log likelihood ratio is negative, then there isgreater confidence that the hard bit is 1. The magnitude of the loglikelihood ratio may indicate the degree of confidence.

For the processes 200, 300, and 400, the hard bits and soft bits may beprovided to a soft audio decoder 110 from the demodulator 108. The softaudio decoder 110 may determine whether to decode the digital signalinto a digital audio signal, based on the soft bits, and generate ormute the digital audio signal, such as at steps 210 and 212 of theprocess 200, steps 310 and 312 of the process 300, and steps 410 and 412of the process 400. The soft audio decoder 110 may utilize softthreshold decoding or softbit decoding to determine whether to decodethe digital signal into the audio signal.

In the embodiment of the soft audio decoder 110 related to softthreshold decoding, a subset of the bits of the audio codeword may bedesignated as having a high perceptual importance. This subset ofcodeword bits may represent a perceptually important frequency rangeand/or a minimally perceptually acceptable audio signal-to-noise ratio(SNR). The subset of the codeword bits designated as having the highperceptual importance may ultimately be decoded into audio, as describedbelow.

Regarding examining the frequency response to designate codeword bits ashaving a high perceptual importance, the process 500 shown in FIG. 5 maybe utilized to determine whether to decode or mute the digital signalbased on the soft bits, such as steps 210 and 212 of the process 200,steps 310 and 312 of the process 300, and steps 410 and 412 of theprocess 400. A typical frequency range for human hearing may be fromapproximately 0-24 kHz. However, certain frequency ranges can be deemedto have a higher perceptual importance than other frequency ranges. Forexample, if the audio is in a first frequency range, e.g., 0-12 kHz, thecorresponding codeword bits in the digital signal can be assigned tohave a high perceptual importance. In this example, audio with afrequency greater than 12 kHz may be deemed as less important since suchaudio is typically more difficult to hear. As another example, thecodeword bits corresponding to audio in a frequency range of 0-6 kHz canbe assigned to have a high perceptual importance, while audio with afrequency greater than 6 kHz may be deemed to be less important. Otherfrequency ranges for determining the perceptual importance of audio arepossible and contemplated. In addition, although two frequency rangesare described above, more than two frequency ranges may be utilized,e.g., 0-8 kHz as one class of high perceptual importance, 8-16 kHz asanother class of high perceptual importance, and 16-24 kHz as not havinga high perceptual importance.

In the case of coded audio and examining the frequency response, thesoft audio decoder 110 may decode the digital signal into codeword bits,such as at step 502 of the process 500 shown in FIG. 5. The soft audiodecoder 110 may identify subsets of the codeword bits that representhigh perceptual importance and low perceptual importance of the audiosignal, such as at step 504. The log likelihood ratios (as representedby the soft bits) associated with each of the subsets may be compared toa predetermined threshold, such as at step 506. If the log likelihoodratio associated with the designated subset having a high perceptualimportance is greater than or equal to the predetermined threshold, thenthe soft audio decoder 110 may generate a codeword based on the hardbits, such as at step 508. On the other hand, the soft audio decoder 110may generate a zero sample codeword, such as at step 512, if the loglikelihood ratio associated with the designated subset having a highperceptual importance is less than the predetermined threshold. The softaudio decoder 110 may also generate a partial zero sample codeword, suchas at step 516, for the subset of the codeword bits that has a lowperceptual importance, if the log likelihood ratio associated with thedesignated subset having a low perceptual importance is less than thepredetermined threshold. Therefore, for coded audio, the resultingoutput audio signal may be based on the hard bits, a mute (zero samplecodeword), or perceptually important bits with the less important bitsmuted.

Regarding the SNR of the audio as a quality for perceptual grading, theprocess 600 shown in FIG. 6 may be utilized to determine whether todecode or mute the digital signal based on the soft bits, such as steps210 and 212 of the process 200, steps 310 and 312 of the process 300,and steps 410 and 412 of the process 400. The perceptually importantbits may be the codeword bits whose correct transmission will produce aperceptually acceptable (but decreased) audio SNR. In other words, ifonly the perceptually important bits of a codeword can be decoded, theremay be a reduction in audio SNR as compared to the case when all bits ofa codeword can be successfully decoded. For example, in an 8 bitcodeword, the four most significant bits may achieve 24 dB of audio SNRand these bits would be considered to be perceptually important. In thisexample, the four least significant bits of the codeword may representan additional 24 dB of audio SNR, assuming that the four perceptuallyimportant bits are successfully transmitted. In this case, the fourleast significant bits may be deemed as less important because the first24 dB of audio SNR is more perceptually relevant than the step from 24dB to 48 dB.

The soft audio decoder 110 may decode the digital signal into codewordbits, such as at step 602 of the process 600 shown in FIG. 6. The softaudio decoder 110 may identify, such as at step 604, a first subset ofthe codeword bits that represents the audio signal with a minimallyperceptually acceptable SNR and a second subset of the codeword bitsthat represents the audio signal with an SNR in excess of the minimallyperceptually acceptable SNR established by the first subset. The loglikelihood ratios (as represented by the soft bits) associated with eachof the subsets may be compared to a predetermined threshold, such as atstep 606. If the log likelihood ratio associated with the first subsetis greater than or equal to the predetermined threshold, then the softaudio decoder 110 may generate a codeword based on the hard bits, suchas at step 608. On the other hand, the soft audio decoder 110 maygenerate a zero sample codeword, such as at step 612, if the loglikelihood ratio associated with the first subset is less than thepredetermined threshold. The soft audio decoder 110 may also generate apartial zero sample codeword, such as at step 616, for the subset of thecodeword bits that has a low perceptual importance, if the loglikelihood ratio associated with the second subset is less than thepredetermined threshold.

In the case of uncoded audio, such as PCM audio, all of the bits haveequal importance. In this case, the process 700 shown in FIG. 7 may beutilized to determine whether to decode or mute the digital signal basedon the soft bits, such as steps 210 and 212 of the process 200, steps310 and 312 of the process 300, and steps 410 and 412 of the process400. The soft audio decoder 110 may decode the digital signal into bits,such as at step 702 of the process 700. The log likelihood ratio (asrepresented by the soft bits) associated with the PCM audio may becompared to a predetermined threshold, such as at step 704. If the loglikelihood ratio associated with the PCM audio is greater than or equalto a predetermined threshold, then the soft audio decoder 110 maygenerate a PCM audio sample based on the hard bits, such as at step 706.However, the soft audio decoder 110 may generate a zero PCM audio sampleif the log likelihood ratio is associated with the PCM audio is lessthan the predetermined threshold, such as at step 710. Therefore, foruncoded audio, the resulting output audio signal may either be based onthe hard bits or a mute (the zero PCM audio sample).

The predetermined threshold used by the soft audio decoder 110 may bedetermined empirically. For example, models may be utilized to determinethe correlation between log likelihood ratio values and actual errors sothat a threshold can be chosen that maximizes the identification oferrors while minimizing false positives (i.e., an error-free bit with alog likelihood ratio below the threshold). As another example, thethreshold may be determined based on subjective standards by evaluatingthe behavior of an audio codec when errors are introduced into thedigital signal.

In the embodiment of the soft audio decoder 110 related to softbitdecoding, the soft audio decoder 110 may generate codewords from thedigital signal or zero sample codewords, based on the bit-wise loglikelihood ratio values (i.e., the soft bits) and a priori knowledge ofthe distribution of codewords, such as the likelihood of each of thepossible codewords. The distribution of the codewords may have beenpreviously generated or computed in real time using short-timehistograms. Softbit decoding is only applicable to coded audio thatutilized audio codecs.

The soft audio decoder 110 may use the log likelihood ratio values todetermine transition probabilities, i.e., the likelihood of a receivedcodeword over the set of all possible transmitted codewords. Thetransition probabilities and the distribution of the codewords can thenbe utilized by the soft audio decoder 110 to generate a posterioriprobabilities that denote the likelihood of each of the possiblecodewords given the received codeword. The soft audio decoder 110 canoutput the most likely codeword based on these probabilities.

A mute may result from softbit decoding in the case when the magnitudeof the log likelihood ratio is small, indicating a low confidence in thehard bits. For example, the audio codec may belong to a class known asadaptive differential pulse code modulation (ADPCM). For this type ofcodec, the a priori knowledge of the distribution of codewords isheavily weighted to the center of the codeword range, which correspondsto silence. As such, when the magnitude of the log likelihood ratio isrelatively small, the softbit decoder would output a codeword thatresults in a muting of the audio.

Regardless of whether the soft audio decoder 110 utilizes soft thresholddecoding or softbit decoding, if the soft audio decoder 110 generates acodeword or PCM audio sample (denoting that audio should be generated),then an audio codec/processor 112 may generate a digital audio signalbased on the codeword or PCM audio sample, such as at step 214 of theprocess 200, step 314 of the process 300, or step 414 of the process400. In particular, these steps are specifically shown in steps 510 and518 of FIG. 5, steps 610 and 618 of FIG. 6, and step 708 of FIG. 7. Inthe case of FIGS. 5 and 6, the digital audio signal may be generatedbased on a codeword having hard bits (steps 510 and 610) or based on acodeword having hard bits and zero sample bits (steps 518 and 618). Inthe case of FIG. 7, the digital audio signal may be generated based onthe PCM audio sample (step 708).

However, if the soft audio decoder 110 generates a zero sample codewordor zero PCM audio sample (denoting that the audio should be muted), thenthe audio codec/processor 112 may mute the audio signal, such as at step216 of the process 200, step 316 of the process 300, or step 416 of theprocess 400. In particular, these steps are specifically shown in step514 of FIG. 5, step 614 of FIG. 6, and step 712 of FIG. 7. In the caseof FIGS. 5 and 6, the digital audio signal may be muted based on acodeword having a zero sample codeword (steps 514 and 614), and in thecase of FIG. 7, the digital audio signal may be muted based on the zeroPCM audio sample (step 712). In some embodiments, the output digitalaudio signal from the audio codec/processor 112 may be converted into anoutput analog audio signal 116 by a digital to analog converter 114. Theoutput analog audio signal 116 may be utilized as desired, such as beingfurther processed by downstream equipment (e.g., mixers, recorders,etc.), played on loudspeakers, etc.

Any process descriptions or blocks in figures should be understood asrepresenting modules, segments, or portions of code which include one ormore executable instructions for implementing specific logical functionsor steps in the process, and alternate implementations are includedwithin the scope of the embodiments of the invention in which functionsmay be executed out of order from that shown or discussed, includingsubstantially concurrently or in reverse order, depending on thefunctionality involved, as would be understood by those having ordinaryskill in the art.

This disclosure is intended to explain how to fashion and use variousembodiments in accordance with the technology rather than to limit thetrue, intended, and fair scope and spirit thereof. The foregoingdescription is not intended to be exhaustive or to be limited to theprecise forms disclosed. Modifications or variations are possible inlight of the above teachings. The embodiment(s) were chosen anddescribed to provide the best illustration of the principle of thedescribed technology and its practical application, and to enable one ofordinary skill in the art to utilize the technology in variousembodiments and with various modifications as are suited to theparticular use contemplated. All such modifications and variations arewithin the scope of the embodiments as determined by the appendedclaims, as may be amended during the pendency of this application forpatent, and all equivalents thereof, when interpreted in accordance withthe breadth to which they are fairly, legally and equitably entitled.

1. A method of receiving an audio signal represented by a digitalsignal, comprising: detecting a phase trajectory associated with apartial response non-linear phase modulation scheme in the digitalsignal from a received RF signal; determining a likely transmitted phasetrajectory based on running the detected phase trajectory through aViterbi algorithm; generating hard bits based on the determined likelytransmitted phase trajectory; generating soft bits based on a degree ofcloseness of the phase trajectory to known legal phase trajectoriesdetermined from running the phase trajectory through a soft-outputViterbi algorithm; determining whether to decode the digital signal intoa digital audio signal, based on the soft bits; generating the digitalaudio signal based on the digital signal, if it is determined to decodethe digital signal into the digital audio signal; and generating a muteddigital audio signal, if it is determined not to decode the digitalsignal into the digital audio signal.
 2. The method of claim 1, whereingenerating the soft bits comprises determining an approximate loglikelihood ratio indicating a confidence in a strength of the generatedhard bits, based on the degree of closeness of the phase trajectory toknown legal phase trajectories.
 3. The method of claim 2, whereindetermining whether to decode the digital signal into the digital audiosignal comprises: decoding the digital signal into codeword bits;identifying a first subset of the codeword bits representing a highperceptual importance of the audio signal and a second subset of thecodeword bits representing a low perceptual importance of the audiosignal; generating a codeword including the hard bits, if the magnitudeof the approximate log likelihood ratio associated with the first subsetis greater than or equal to a predetermined threshold; and generatingthe codeword with zero sample bits, if the magnitude of the approximatelog likelihood ratio associated with the first subset is less than thepredetermined threshold; and generating the codeword including the hardbits and the zero sample bits, if the magnitude of the log likelihoodratio associated with the second subset is less than the predeterminedthreshold.
 4. The method of claim 3, wherein: generating the digitalaudio signal comprises generating the digital audio signal based on thecodeword including the hard bits, if the magnitude of the log likelihoodratio associated with the first subset is greater than or equal to apredetermined threshold; generating the muted digital audio signalcomprises generating the muted digital audio signal based on thecodeword with the zero sample bits, if the magnitude of the loglikelihood ratio associated with the first subset is less than thepredetermined threshold; and generating the digital audio signalcomprises generating the digital audio signal based on the codewordincluding the hard bits and the zero sample bits, if the magnitude ofthe log likelihood ratio associated with the second subset is less thanthe predetermined threshold.
 5. The method of claim 2, wherein:determining whether to decode the digital signal into the digital audiosignal comprises: decoding the digital signal into bits; generating aPCM audio sample from the bits, if the magnitude of the approximate loglikelihood ratio associated with the bits is greater than or equal to apredetermined threshold; and generating a zero PCM audio sample, if themagnitude of the approximate log likelihood ratio associated with thebits is less than the predetermined threshold; generating the digitalaudio signal comprises generating the digital audio signal based on thePCM audio sample, if the magnitude of the approximate log likelihoodratio associated with the bits is greater than or equal to apredetermined threshold; and generating the muted digital audio signalcomprises generating the muted digital audio signal based on the zeroPCM audio sample, if the magnitude of the approximate log likelihoodratio associated with the bits is less than the predetermined threshold.6. The method of claim 2, wherein determining whether to decode thedigital signal into the digital audio signal comprises: decoding thedigital signal into codeword bits; identifying a first subset of thecodeword bits representing the audio signal with a minimallyperceptually acceptable signal-to-noise ratio (SNR) and second subset ofthe codeword bits representing the audio signal with an SNR in excess ofthe minimally perceptually acceptable SNR established by the firstsubset; generating a codeword including the hard bits, if the magnitudeof the approximate log likelihood ratio associated with the first subsetis greater than or equal to a predetermined threshold; and generatingthe codeword with zero sample bits, if the magnitude of the approximatelog likelihood ratio associated with the first subset is less than thepredetermined threshold; and generating the codeword including the hardbits and the zero sample bits, if the magnitude of the log likelihoodratio associated with the second subset is less than the predeterminedthreshold.
 7. The method of claim 6, wherein: generating the digitalaudio signal comprises generating the digital audio signal based on thecodeword including the hard bits, if the magnitude of the log likelihoodratio associated with the first subset is greater than or equal to apredetermined threshold; generating the muted digital audio signalcomprises generating the muted digital audio signal based on thecodeword with the zero sample bits, if the magnitude of the loglikelihood ratio associated with the first subset is less than thepredetermined threshold; and generating the digital audio signalcomprises generating the digital audio signal based on the codewordincluding the hard bits and the zero sample bits, if the magnitude ofthe log likelihood ratio associated with the second subset is less thanthe predetermined threshold.
 8. The method of claim 1: furthercomprising: decoding the digital signal encoded with a forward errorcorrection (FEC) code; and modifying the soft bits based on the decodeddigital signal; wherein determining whether to decode the digital signalcomprises determining whether to decode the digital signal into thedigital audio signal, based on the modified soft bits.
 9. A system forreceiving an audio signal represented by a digital signal, comprising:(1) a detector configured for detecting a phase trajectory associatedwith a partial response non-linear phase modulation scheme in thedigital signal from a received RF signal; (2) a demodulator configuredfor: determining a likely transmitted phase trajectory based on runningthe detected phase trajectory through a Viterbi algorithm; generatinghard bits based on the determined likely transmitted phase trajectory;and generating soft bits based on a degree of closeness of the phasetrajectory to known legal phase trajectories determined from running thephase trajectory through a soft-output Viterbi algorithm; (3) a softaudio decoder configured for determining whether to decode the digitalsignal into a digital audio signal, based on the soft bits; and (4) anaudio codec/processor configured for: generating the digital audiosignal based on the digital signal, if it is determined to decode thedigital signal into the digital audio signal; and generating a muteddigital audio signal, if it is determined not to decode the digitalsignal into the digital audio signal.
 10. The system of claim 9, whereinthe demodulator is configured for generating the soft bits bydetermining an approximate log likelihood ratio indicating a confidencein a strength of the generated hard bits, based on the degree ofcloseness of the phase trajectory to known legal phase trajectories. 11.The system of claim 10, wherein the soft audio decoder is configured fordetermining whether to decode the digital signal into the digital audiosignal by: decoding the digital signal into codeword bits; identifying afirst subset of the codeword bits representing a high perceptualimportance of the audio signal and a second subset of the codeword bitsrepresenting a low perceptual importance of the audio signal; generatinga codeword including the hard bits, if the magnitude of the approximatelog likelihood ratio associated with the first subset is greater than orequal to a predetermined threshold; and generating the codeword withzero sample bits, if the magnitude of the approximate log likelihoodratio associated with the first subset is less than the predeterminedthreshold; and generating the codeword including the hard bits and thezero sample bits, if the magnitude of the log likelihood ratioassociated with the second subset is less than the predeterminedthreshold.
 12. The system of claim 11, wherein the audio codec/processoris configured for: generating the digital audio signal by generating thedigital audio signal based on the codeword including the hard bits, ifthe magnitude of the log likelihood ratio associated with the firstsubset is greater than or equal to a predetermined threshold; generatingthe muted digital audio signal by generating the muted digital audiosignal based on the codeword with the zero sample bits, if the magnitudeof the log likelihood ratio associated with the first subset is lessthan the predetermined threshold; and generating the digital audiosignal by generating the digital audio signal based on the codewordincluding the hard bits and the zero sample bits, if the magnitude ofthe log likelihood ratio associated with the second subset is less thanthe predetermined threshold.
 13. The system of claim 10, wherein: thesoft audio decoder is configured for determining whether to decode thedigital signal into the digital audio signal by: decoding the digitalsignal into bits; generating a PCM audio sample from the bits, if themagnitude of the approximate log likelihood ratio associated with thebits is greater than or equal to a predetermined threshold; andgenerating a zero PCM audio sample, if the magnitude of the approximatelog likelihood ratio associated with the bits is less than thepredetermined threshold; the audio codec/processor is configured forgenerating the digital audio signal by generating the digital audiosignal based on the PCM audio sample, if the magnitude of theapproximate log likelihood ratio associated with the bits is greaterthan or equal to a predetermined threshold; and the audiocodec/processor is configured for generating the muted digital audiosignal by generating the muted digital audio signal based on the zeroPCM audio sample, if the magnitude of the approximate log likelihoodratio associated with the bits is less than the predetermined threshold.14. The system of claim 10, wherein the soft audio decoder is configuredfor determining whether to decode the digital signal into the digitalaudio signal by: decoding the digital signal into codeword bits;identifying a first subset of the codeword bits representing the audiosignal with a minimally perceptually acceptable signal-to-noise ratio(SNR) and second subset of the codeword bits representing the audiosignal with an SNR in excess of the minimally perceptually acceptableSNR established by the first subset; generating a codeword including thehard bits, if the magnitude of the approximate log likelihood ratioassociated with the first subset is greater than or equal to apredetermined threshold; and generating the codeword with zero samplebits, if the magnitude of the approximate log likelihood ratioassociated with the first subset is less than the predeterminedthreshold; and generating the codeword including the hard bits and thezero sample bits, if the magnitude of the log likelihood ratioassociated with the second subset is less than the predeterminedthreshold.
 15. The system of claim 14, wherein the audio codec/processoris configured for: generating the digital audio signal by generating thedigital audio signal based on the codeword including the hard bits, ifthe magnitude of the log likelihood ratio associated with the firstsubset is greater than or equal to a predetermined threshold; generatingthe muted digital audio signal by generating the muted digital audiosignal based on the codeword with the zero sample bits, if the magnitudeof the log likelihood ratio associated with the first subset is lessthan the predetermined threshold; and generating the digital audiosignal by generating the digital audio signal based on the codewordincluding the hard bits and the zero sample bits, if the magnitude ofthe log likelihood ratio associated with the second subset is less thanthe predetermined threshold.
 16. The system of claim 10: furthercomprising a forward error correction (FEC) decoder configured for:decoding the digital signal encoded with an FEC code; and modifying thesoft bits based on the decoded digital signal; wherein the soft audiodecoder is configured for determining whether to decode the digitalsignal by determining whether to decode the digital signal into thedigital audio signal, based on the modified soft bits.